Senior Manager, Data Science, Model Risk Office

Capital One Financial

Confirmed live yesterday Low trust

Quick summary

Work type
On-site
Location
McLean, VARichmond, VAChicago, IL
Salary
$209,000–$238,500 / yr
Posted
128 days ago
Freshness
Confirmed live yesterday
Nearby
99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $199k
This role $224k
$148k most similar roles pay here $248k

This role pays more than 70% of similar roles. Most pay $162,000–$235,550 — the shaded band above. At the midpoint, this role pays about $224k versus about $199k for comparable roles.

Based on 240 similar postings.

Employer

About Capital One Financial

Capital One Financial is a bank holding company specializing in credit cards, auto loans, banking, and savings products, known for its data-driven approach to consumer and commercial finance. Industry: Financial Services & Banking

Capital One Financial currently has 998 open roles on FindRole.

Listed pay typically runs $197,300–$225,100 across 992 roles with salary data.

Most-posted roles

View all roles at Capital One Financial

At a glance

TL;DR · Senior Manager, Data Science, Model Risk Office

Role Posting Log in to save

Senior Manager, Data Science - Model Risk Office joins the Model Risk Office team to safeguard the company from model failures while enhancing decision-making across various business domains. This role involves partnering with cross-functional teams of data scientists, software engineers, and product managers to identify and quantify risks associated with models, including those involving Generative AI. The successful candidate will build machine learning models to challenge current production "champion" models and contribute to the model governance framework. Day-to-day tasks include validating diverse models and presenting risk impacts to executives. Required skills include proficiency in PyTorch, Hugging Face, LangChain, Vector Databases, LLMOps, and observability platforms. The role requires expertise in Python, Scala, or R, as well as experience with relational databases, cloud computing, clustering, classification, sentiment analysis, time series, and deep learning to manage large volumes of multi-modal data.

Skills

Machine Learning Python PyTorch Hugging Face LangChain Vector Databases LLMOps AWS Relational Databases Deep Learning Time Series Sentiment Analysis Clustering Classification Statistics Cloud Computing Data Analytics

What you'll do

  • Identify and quantify risks associated with models in collaboration with cross-functional teams.
  • Utilize tools like PyTorch, Hugging Face, and LangChain to extract insights from multi-modal data.
  • Build machine learning models to challenge and test "champion models" currently in production.
  • Contribute to the model governance framework for next-generation machine learning systems.
  • Validate a wide range of models across multiple business domains within Enterprise Services.
  • Present identified model risks and their potential business impacts to executive leadership.
  • Research and evaluate emerging technologies to improve internal data science capabilities.

What we're looking for

  • A Bachelor's degree in a quantitative field plus 7 years of experience performing data analytics.
  • A Master's degree or MBA in a quantitative field plus 5 years of experience performing data analytics.
  • A PhD in a quantitative field plus 2 years of experience performing data analytics.
  • At least 2 years of experience leveraging open source programming languages for large scale data analysis.
  • At least 2 years of experience working with machine learning.
  • At least 2 years of experience utilizing relational databases.
  • At least 5 years of experience in Python, Scala, or R for large scale data analysis.
  • At least 1 year of experience working with AWS and managing people.

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